Repeated naloxone-induced morphine withdrawal alters blood brain barrier and blood spinal cord barrier integrity in mice
Bibliographic record
Abstract
Passage of molecules across the central nervous system is tightly regulated by the blood-brain barrier (BBB) and blood-spinal cord barrier (BSCB), which restrict entry of many substances, including opioid medications. Here, we examined the effects of opioid withdrawal on BBB and BSCB integrity by measuring extravascular levels of peripherally injected dyes - Evans Blue (high molecular weight) and sodium fluorescein (NaFl, low molecular weight) - in the brain and spinal cord. In morphine-dependent male and female mice, repeated naloxone challenge induced robust withdrawal behaviors concomitant with region specific dye extravasation. In a fixed dose morphine paradigm, Evans Blue extravasation was highest within the cortex, hippocampus, cerebellum, and brainstem (pons and medulla) in male mice, and in the hypothalamus in female mice. By contrast, NaFl extravasation remained unchanged in both sexes. In an escalating dose morphine paradigm, Evans Blue extravasation was most prominent in the brainstem (pons and medulla) of both sexes, as well as in the lumbar of male mice and cervical spinal cord of female mice. NaFl extravasation in these regions was unchanged in male but reduced in female mice. These findings suggest that repeated opioid withdrawal alters permeability of the BBB and BSCB in discrete regions of the brain and spinal cord.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".